شماره ركورد كنفرانس :
1946
عنوان مقاله :
Fault Diagnosis of Electromotor of SAR-7 Hydraulic Pump by an Intelligent Combined Method Based on k-Nearest Neighbor and Improved Distance Evaluation
عنوان به زبان ديگر :
Fault Diagnosis of Electromotor of SAR-7 Hydraulic Pump by an Intelligent Combined Method Based on k-Nearest Neighbor and Improved Distance Evaluation
پديدآورندگان :
Bagheri B نويسنده University of Tehran - Department of Mechanical Engineering of Agricultural Machinery - MSc student , Ahmadi Hojat نويسنده University of Tehran - Department of Mechanical Engineering of Agricultural Machinery - Associate Professor , Labbafi R نويسنده University of Tehran - Department of Mechanical Engineering of Agricultural Machinery - MSc student
كليدواژه :
Fault diagnosis , Feed forward neural networks , feature extraction , Signal Processing , Vibrations
عنوان كنفرانس :
ششمين كنفرانس نگهداري و تعميرات ايران
چكيده لاتين :
In present paper, an electro-motor of a Search and Rescue (SAR-7) is studied by its frequency domain signals. Vibration Signals gained from electro-motor while its daily work. Some statistical parameters are used for data mining from raw signals and the Improved Distance Evaluation (IDE) technique is used for feature extraction. Variant thresholds for IDE are used to study the effect of this feature selection algorithm on overall performance of classification by k-Nearest neighbor (kNN) algorithm. Variable k value is used in order to make effect of IDE independent from classifier settings. Behavior of kNN performance depending variable k value between 1 and 10 is like descending linear function. As results, IDE made calculations faster and increased overall performance for fault classification with kNN.
شماره مدرك كنفرانس :
4490281
